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首页> 外文期刊>BMC Medical Genomics >Integrative analyses of proteomics and RNA transcriptomics implicate mitochondrial processes, protein folding pathways and GWAS loci in Parkinson disease
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Integrative analyses of proteomics and RNA transcriptomics implicate mitochondrial processes, protein folding pathways and GWAS loci in Parkinson disease

机译:蛋白质组学和RNA转录组学的综合分析涉及帕金森病的线粒体过程,蛋白质折叠途径和GWAS基因座

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Background Parkinson disease (PD) is a neurodegenerative disease characterized by the accumulation of alpha-synuclein (SNCA) and other proteins in aggregates termed “Lewy Bodies” within neurons. PD has both genetic and environmental risk factors, and while processes leading to aberrant protein aggregation are unknown, past work points to abnormal levels of SNCA and other proteins. Although several genome-wide studies have been performed for PD, these have focused on DNA sequence variants by genome-wide association studies (GWAS) and on RNA levels (microarray transcriptomics), while genome-wide proteomics analysis has been lacking. Methods This study employed two state-of-the-art technologies, three-stage Mass Spectrometry Tandem Mass Tag Proteomics (12 PD, 12 controls) and RNA-sequencing transcriptomics (29 PD, 44 controls), evaluated in the context of PD GWAS implicated loci and microarray transcriptomics (19 PD, 24 controls). The technologies applied for this study were performed in a set of overlapping prefrontal cortex (Brodmann area 9) samples obtained from PD patients and sex and age similar neurologically healthy controls. Results After appropriate filters, proteomics robustly identified 3558 unique proteins, with 283 of these (7.9?%) significantly different between PD and controls (q-value?Conclusions We report the largest analysis of proteomics in PD to date, and the first to combine this technology with RNA-sequencing to investigate GWAS implicated loci. Notably, differentially expressed protein-coding genes were more likely to not be characterized in the proteomics analysis, which lessens the ability to compare across platforms. Combining multiple genome-wide platforms offers novel insights into the pathological processes responsible for this disease by identifying pathways implicated across methodologies.
机译:背景帕金森病(PD)是一种神经退行性疾病,其特征在于α-突触核蛋白(SNCA)和其他蛋白质在神经元内聚集在称为“路易体”的聚集物中。 PD具有遗传和环境风险因素,虽然导致异常蛋白质聚集的过程尚不清楚,但过去的工作表明SNCA和其他蛋白质的含量异常。尽管已经针对PD进行了几项全基因组研究,但通过全基因组关联研究(GWAS)和RNA水平(微阵列转录组学),这些研究集中在DNA序列变异上,而缺乏全基因组蛋白质组学分析。方法该研究采用了两种最新技术,即三阶段质谱串联质谱标签蛋白质组学(12个PD,12个对照)和RNA测序转录组学(29个PD,44个对照),在PD GWAS的背景下进行了评估涉及的基因座和微阵列转录组学(19 PD,24个对照)。本研究中使用的技术是在一组重叠的前额叶皮层(Brodmann区域9)样本中进行的,样本来自PD患者以及性别和年龄相似的神经系统健康对照。结果经过适当的过滤后,蛋白质组学可靠地鉴定出3558种独特的蛋白质,其中283种(7.9?%)的PD和对照之间存在显着差异(q值)。这项利用RNA测序技术研究GWAS的基因座的方法。值得注意的是,差异表达的蛋白质编码基因很可能在蛋白质组学分析中无法表征,从而降低了跨平台比较的能力。通过确定跨方法论的途径,将其纳入造成该疾病的病理过程。

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